Data Analytics (with Professional Experience) (MSc)

University of Portsmouth the United Kingdom

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The award
MSc

How long you will study
18 Months

Domestic course fees
find out

How you will study
full-time

Course starts
September

International course fees
find out

All study options

About Data Analytics (with Professional Experience) at University of Portsmouth

Overview

Do you want to get professional workplace experience of data analytics while qualifying with a Master's degree in the field?

On this MSc Data Analytics (with Professional Experience) degree course, you'll combine a 6-month work placement or a professional experience module with taught modules that develop your skills in data analysis, and the application and management of big data. You'll see how you can apply data analytics tools in emerging technologies and start-ups using the UK's only university-based SAP Next Gen Lab.

When you complete the course successfully, your Master's degree and professional experience could lead to career opportunities in areas such as data science and engineering, financial data analytics, social media analysis, political data analysis and cybersecurity.

What you'll experience

On this Data Analytics (with Professional Experience) MSc degree you'll:

  • Use the UK's only university-based SAP Next Gen Lab, featuring the world's leading cloud-based business software
  • Work on your technological and technical abilities
  • Build your previous studies and experience to postgraduate level
  • Master the big data and data mining tools you need for your career such as Python, R and machine learning
  • Analyse data from the University's original research in cosmology, health informatics and cybersecurity
  • Develop your knowledge of applied data analytics and engineering, big data, business intelligence, and advanced data management
  • Engage with important topics, such as the use of emerging technologies in data mining, business intelligence, machine learning and big data
  • Plan and develop an in-depth research project, using your analytical skills to demonstrate understanding beyond taught material

What you'll study on this MSc Data Analytics degree course

On this Master's degree in Data Analytics course, you'll study modules worth 190 credits.

The core modules are:

  • Applied data and text analytics
  • Big data applications
  • Business intelligence
  • Data management
  • Master's engineering or study project

There are no optional modules on this course.

We use the best and most current research and professional practice alongside feedback from our students to make sure course content is relevant to your future career or further studies.

Therefore, some course content may change over time to reflect changes in the discipline or industry.

6-month professional experience module

In this module, you'll do a work placement or a professional experience programme. You'll do this for 6 months between September and March after you've completed your year of taught studies.

Work placement

When on placement you'll have the opportunity to get involved in information systems research events and initiatives.

You can begin looking and applying for placements after completing your first teaching block. You'll get support from the Careers and Employability Centre and the Faculty of Technology Student Placement and Employability Centre in enhancing your employability skills, and in identifying and applying for suitable placements.

Note that work placements can't be guaranteed because it depends on their availability and the specific needs of placement providers. We'll give you the support you need to identify work placements but you'll be responsible for securing a placement successfully.

Professional experience programme

If you're unable to secure a work placement, you'll complete a professional experience programme designed to meet your career aspirations.

You'll further develop your employability and enterprise skills and prepare yourself for the workplace. This could be an entrepreneurship, industrial-related or consultancy project, or other activities appropriate for your career development.

Teaching

This Data Analytics Master's degree adopts an innovative teaching style in the core units. There are no traditional lectures. Instead, lectures and practical classes are combined in long applied workshop sessions. 

All teaching takes place in our computer labs, which are equipped with a variety of data analytics and data mining tools.

Teaching staff include experienced experts with relevant industry experience and research experience in data science, machine learning and big data subject areas. Teaching staff have worked in national and international companies as software engineers, data scientists and big data programmers.

You can access all teaching resources on Moodle, our virtual learning environment, from anywhere with a Web connection.

For more about the teaching activities for specific modules, see the module list above.

How you're assessed

You’ll be assessed through:

  • written coursework
  • practical assessments
  • exams

You’ll be able to test your skills and knowledge informally before you do assessments that count towards your final mark. You can get feedback on all practice and formal assessments so you can improve in the future.

Careers and opportunities

Data is a big source of economic value to businesses, government and individuals and the ability to analyse big data is expected to be one of the most sought-after skills over the next few decades. So this Master's in Data Analytics can significantly improve your career prospects.

In addition, this course focuses on your application and use of the latest data analytics and mining tools while on a professional experience placement. This adds to the tools and techniques you'll develop during workshops in our SAP Next Gen Lab and on our supercomputer.

When you finish the course, our Careers and Employability service can help you find a job that puts your skills to work. You can get help, advice and support from our Careers and Employability service for up to 5 years after you leave the University as you advance in your career.

What can you do with a Master's in Data Analytics?

Previous graduates have gone on to work in areas including:

  • data science and engineering
  • business intelligence
  • programming
  • financial data analytics
  • cybersecurity data scientist/analyst
  • health care informatics
  • social media analysis
  • political data analysis

You can also use your Data Analytics MSc to get entry to higher-level professional qualifications such as British Computer Society accreditation.

What jobs can you do with a Master's in Data Analytics?

Roles our graduates have taken on include:

  • senior data scientist
  • data engineer
  • business intelligence analyst
  • programmer
  • machine learning programmer
  • PhD researcher
  • machine learning programmer
  • big data programmers and engineers

What's the future demand for data analytics graduates?

There's an increasing business demand for employees with data analysis, technical and soft skills. According to IBM, 90% of human data was made in the last 2 years and according to the Future of Jobs Report 2018, 85% of companies are likely or very likely to be using big data analytics.

New technologies in the data science field allow us to extract knowledge and value from this escalation in data and apply it to fields such as finance, cybersecurity, health care, social media analysis, politics and more. This means employers are increasingly looking for people who can deal with large data sets, understand business problems and bring people together to come up with solutions.

Study options for this course

  • The award How you will study How long you will study Course starts Domestic course fees International course fees
  • The awardMScHow you will studyFull-timeHow long you will study18 months
    Course startsSeptemberDomestic course fees find outInternational course fees find out

Notes about fees for this course

https://www.port.ac.uk/study/masters-and-postgraduate-taught/fees-and-funding

Entry requirements

A second-class honours degree in a relevant subject, or equivalent professional experience.

English language proficiency at a minimum of IELTS band 6.0 with no component score below 6.0.

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